Systems for receiving and analyzing sound signals, for example, undersea sonar systems, utilize multiple transducers in a variety of configurations to receive and process sound signals from the environment. Detected sounds may indicate the presence of a friendly or enemy vessel. Sound signatures associated with each type of sound may be used to correlate the detected sound and aid in identifying its source. In addition to the sound signals associated with a particular target, other sound sources emit signals that may be received by the transducers. For example, the sound of water flowing past the sonar array, or vibrations from structural elements within the array, may generate sound waves that are also detectable by the sonar array. These sound signals are referred to as self-noise. Self-noise interferes with the straightforward identification of target sounds and therefore should be identified and removed from the overall signals received.
The presence of self noise may compromise the ability to effectively detect remote targets. Structural and flow self-noise often travel at sub-sonic speeds (i.e. less than the speed of sound in water). One aspect of wavenumber-frequency (kω) analysis allows for the separation of sub-sonic noise sources from sonic noise sources. Sub-sonic noise sources may be identified by their propagation characteristics or a known acoustic signature. Accurate identification of the self-noise sources allows for compensation or remediation of the noise, enabling better identification of target sounds.
One and two dimensional wavenumber-frequency analysis provides limited information on self-noise sound sources. One-dimensional kω analysis is utilized for linear sonar arrays, for example, a towed linear array or a segment of a curved array using a linear approximation. However, one-dimensional kω analysis only accounts for the kx component of k and the frequency. Thus the ky and kz components remain unaccounted for. The lack of these k components result in ambiguities with respect to the direction of arrival of a detected self-noise sound source. Similarly, in two-dimensional kω analysis, only the kx and ky components of k are accounted for. Thus, ambiguities with respect to the kz component of k are extant.
Alternative techniques for identifying self-noise and resolving problems associated with the identification of self noise within an overall received signal containing information associated with a target of interest, is desirable.